hello,
I am trying to implement the bootstrapping to a set of insurance claim data
in triangular form using the ChainLadder package. I want to obtain the
prediction errors of the reserve estimate using the result from
bootstrapping, here is the output:
>BootChainLadder(Triangle = incr2cum(data), R = 1000, process.distr =
"gamma")
BootChainLadder(Triangle = incr2cum(data), R = 1000, process.distr =
"gamma")
Latest Mean Ultimate Mean IBNR SD IBNR IBNR 75%
IBNR 95%
2 36,241 36,241 0
0 0 0
3 47,380 47,619 239
608 341 1,449
4 45,877 47,062 1,185 1,072
1,701 3,149
5 70,696 74,224 3,528
1,850 4,613 6,683
6 83,797 90,749 6,952
2,558 8,580 11,386
7 105,933 116,061 10,128 3,173
12,212 15,464
8 169,428 186,824 17,396 4,783
20,491 25,602
9 158,634 176,267 17,633 4,462
20,446 25,362
10 123,794 139,182 15,388 3,955
17,783 22,368
11 85,531 111,495 25,964 4,697
29,147 33,862
Totals
Latest: 927,311
Mean Ultimate: 1,025,723
Mean IBNR: 98,412
SD IBNR: 18,950
Total IBNR 75%: 111,257
Total IBNR 95%: 128,807
Also, would really appreciate if anyone could explain the abbreviations like
SD IBNR, does it stand for Standard Deviation for IBNR? If so, then can i
use this to find the prediction errors?
Thanks.
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